----------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/006489466/Desktop/CA OIS/SCMReviewerResults.
> log
  log type:  text
 opened on:  24 Aug 2023, 10:26:13

. * Additional analyses for Reviewer 1
. * exclude agencies with most weight to assess sensitivity
. 
. /* 
> 
> So after reviewing donor weights from other places, will only 
> include ones that 
> had zero weights in past analysis:
> 
> *excluded ones for state population rates so will be used in r
> e-analysis
> AR, CO, GA, HA, IA, IL, KY, MD, MN, MO, NC, NB, NH, NJ, NY, OR
> , PA, RI
> SC, SD, TX, UT, VT, WA, WI, WY
> 
> */
. 
. *********************
. ** OIS RATE excluded **
. *********************
. 
. synth oisp oisp(`=tm(2015m1)') oisp(`=tm(2015m2)') oisp(`=tm(2
> 015m3)') ///
> oisp(`=tm(2015m4)') oisp(`=tm(2015m5)') oisp(`=tm(2015m6)') oi
> sp(`=tm(2015m7)') ///
> oisp(`=tm(2015m8)') oisp(`=tm(2015m9)') oisp(`=tm(2015m10)') o
> isp(`=tm(2015m11)') ///
> oisp(`=tm(2015m12)') oisp(`=tm(2016m1)') oisp(`=tm(2016m2)') o
> isp(`=tm(2016m3)') ///
> oisp(`=tm(2016m4)') oisp(`=tm(2016m5)') oisp(`=tm(2016m6)') oi
> sp(`=tm(2016m7)') ///
> oisp(`=tm(2016m8)') oisp(`=tm(2016m9)') oisp(`=tm(2016m10)') o
> isp(`=tm(2016m11)') ///
> oisp(`=tm(2016m12)') oisp(`=tm(2017m1)') oisp(`=tm(2017m2)') o
> isp(`=tm(2017m3)') ///
> oisp(`=tm(2017m4)') oisp(`=tm(2017m5)') oisp(`=tm(2017m6)') oi
> sp(`=tm(2017m7)') ///
> oisp(`=tm(2017m8)') oisp(`=tm(2017m9)') oisp(`=tm(2017m10)') o
> isp(`=tm(2017m11)') ///
> oisp(`=tm(2017m12)') oisp(`=tm(2018m1)') oisp(`=tm(2018m2)') o
> isp(`=tm(2018m3)') ///
> oisp(`=tm(2018m4)') oisp(`=tm(2018m5)') oisp(`=tm(2018m6)') oi
> sp(`=tm(2018m7)') ///
> oisp(`=tm(2018m8)') oisp(`=tm(2018m9)') oisp(`=tm(2018m10)') o
> isp(`=tm(2018m11)') ///
> oisp(`=tm(2018m12)') oisp(`=tm(2019m1)') oisp(`=tm(2019m2)') o
> isp(`=tm(2019m3)') ///
> oisp(`=tm(2019m4)') oisp(`=tm(2019m5)') oisp(`=tm(2019m6)') oi
> sp(`=tm(2019m7)') ///
> oisp(`=tm(2019m8)') oisp(`=tm(2019m9)') oisp(`=tm(2019m10)') o
> isp(`=tm(2019m11)') ///
> oisp(`=tm(2019m12)'), trunit(5) trperiod(`=tm(2020m1)') counit
> (3 6 11 12 13 15 ///
> 18 21 24 25 28 30 31 32 35 38 39 40 41 42 44 45 47 48 49 51) f
> igure 
----------------------------------------------------------------
Synthetic Control Method for Comparative Case Studies
----------------------------------------------------------------

First Step: Data Setup
----------------------------------------------------------------
----------------------------------------------------------------
Data Setup successful
----------------------------------------------------------------
                Treated Unit: CA
               Control Units: AR, CO, GA, HI, IA, IL, KY, MD,
                              MN, MO, NC, NE, NH, NJ, NY, OR,
                              PA, RI, SC, SD, TX, UT, VT, WA,
                              WI, WY
----------------------------------------------------------------
          Dependent Variable: oisp
  MSPE minimized for periods: 660 661 662 663 664 665 666 667
                              668 669 670 671 672 673 674 675
                              676 677 678 679 680 681 682 683
                              684 685 686 687 688 689 690 691
                              692 693 694 695 696 697 698 699
                              700 701 702 703 704 705 706 707
                              708 709 710 711 712 713 714 715
                              716 717 718 719
Results obtained for periods: 660 661 662 663 664 665 666 667
                              668 669 670 671 672 673 674 675
                              676 677 678 679 680 681 682 683
                              684 685 686 687 688 689 690 691
                              692 693 694 695 696 697 698 699
                              700 701 702 703 704 705 706 707
                              708 709 710 711 712 713 714 715
                              716 717 718 719 720 721 722 723
                              724 725 726 727 728 729 730 731
                              732 733 734 735 736 737 738 739
                              740 741 742 743 744 745 746 747
                              748 749 750 751 752 753 754 755
----------------------------------------------------------------
                  Predictors: oisp(660) oisp(661) oisp(662)
                              oisp(663) oisp(664) oisp(665)
                              oisp(666) oisp(667) oisp(668)
                              oisp(669) oisp(670) oisp(671)
                              oisp(672) oisp(673) oisp(674)
                              oisp(675) oisp(676) oisp(677)
                              oisp(678) oisp(679) oisp(680)
                              oisp(681) oisp(682) oisp(683)
                              oisp(684) oisp(685) oisp(686)
                              oisp(687) oisp(688) oisp(689)
                              oisp(690) oisp(691) oisp(692)
                              oisp(693) oisp(694) oisp(695)
                              oisp(696) oisp(697) oisp(698)
                              oisp(699) oisp(700) oisp(701)
                              oisp(702) oisp(703) oisp(704)
                              oisp(705) oisp(706) oisp(707)
                              oisp(708) oisp(709) oisp(710)
                              oisp(711) oisp(712) oisp(713)
                              oisp(714) oisp(715) oisp(716)
                              oisp(717) oisp(718) oisp(719)
----------------------------------------------------------------
Unless period is specified
predictors are averaged over: 660 661 662 663 664 665 666 667
                              668 669 670 671 672 673 674 675
                              676 677 678 679 680 681 682 683
                              684 685 686 687 688 689 690 691
                              692 693 694 695 696 697 698 699
                              700 701 702 703 704 705 706 707
                              708 709 710 711 712 713 714 715
                              716 717 718 719
----------------------------------------------------------------

Second Step: Run Optimization
----------------------------------------------------------------
----------------------------------------------------------------
Optimization done
----------------------------------------------------------------

Third Step: Obtain Results
----------------------------------------------------------------
Loss: Root Mean Squared Prediction Error

---------------------
   RMSPE |  .1257932 
---------------------
----------------------------------------------------------------
Unit Weights:

-----------------------
    Co_No | Unit_Weight
----------+------------
       AR |         .01
       CO |        .106
       GA |        .105
       HI |           0
       IA |           0
       IL |           0
       KY |        .109
       MD |           0
       MN |           0
       MO |        .096
       NC |           0
       NE |        .013
       NH |           0
       NJ |        .041
       NY |           0
       OR |        .004
       PA |           0
       RI |           0
       SC |        .203
       SD |        .009
       TX |        .048
       UT |           0
       VT |           0
       WA |           0
       WI |        .256
       WY |           0
-----------------------
----------------------------------------------------------------
Predictor Balance:

------------------------------------------------------
                               |   Treated  Synthetic 
-------------------------------+----------------------
                     oisp(660) |   .228917   .1839353 
                     oisp(661) |   .228917   .2282695 
                     oisp(662) |   .559575   .3406589 
                     oisp(663) |  .4323989   .3307764 
                     oisp(664) |  .2034818   .2928391 
                     oisp(665) |  .2797875   .1070404 
                     oisp(666) |  .5341398    .405545 
                     oisp(667) |  .4323989   .1957567 
                     oisp(668) |  .4578341   .1971746 
                     oisp(669) |  .5087045   .2378677 
                     oisp(670) |  .4069636   .4166672 
                     oisp(671) |   .559575    .251655 
                     oisp(672) |  .2790371   .2530094 
                     oisp(673) |  .3805051   .2504329 
                     oisp(674) |  .2790371   .2763192 
                     oisp(675) |  .2029361   .3178308 
                     oisp(676) |  .2283031   .2899483 
                     oisp(677) |  .2029361   .4220982 
                     oisp(678) |  .3805051   .3048336 
                     oisp(679) |  .4566061   .4501972 
                     oisp(680) |  .2283031   .2374722 
                     oisp(681) |  .3044041    .219635 
                     oisp(682) |  .3044041   .2585353 
                     oisp(683) |  .2790371   .1156202 
                     oisp(684) |  .4532419   .2968378 
                     oisp(685) |  .2769812   .3812594 
                     oisp(686) |  .4280618   .3085083 
                     oisp(687) |  .2769812   .1971322 
                     oisp(688) |  .4028817    .241562 
                     oisp(689) |  .3525215   .3276019 
                     oisp(690) |  .3525215   .3354832 
                     oisp(691) |  .3777016    .347511 
                     oisp(692) |  .3021613   .2187187 
                     oisp(693) |  .2518011   .3705064 
                     oisp(694) |  .2518011   .2813003 
                     oisp(695) |  .3021613   .2260448 
                     oisp(696) |  .2264951   .4390396 
                     oisp(697) |  .2264951   .2632699 
                     oisp(698) |  .3019935   .3302337 
                     oisp(699) |  .3271596   .3291477 
                     oisp(700) |  .1509968   .3761137 
                     oisp(701) |   .201329   .2679457 
                     oisp(702) |  .3523258   .2407572 
                     oisp(703) |  .3019935   .2774898 
                     oisp(704) |  .1006645   .2572872 
                     oisp(705) |   .201329   .2833832 
                     oisp(706) |  .2516613   .2531601 
                     oisp(707) |  .2768274   .1612917 
                     oisp(708) |  .3023312   .2726528 
                     oisp(709) |  .2771369   .2682294 
                     oisp(710) |  .2267484   .3103533 
                     oisp(711) |  .3023312   .2591891 
                     oisp(712) |  .2519427   .2863007 
                     oisp(713) |  .4283025   .2660858 
                     oisp(714) |  .2267484   .2383152 
                     oisp(715) |  .2771369   .3539912 
                     oisp(716) |  .1763599   .3101069 
                     oisp(717) |  .4031082    .295069 
                     oisp(718) |  .2015541    .473199 
                     oisp(719) |  .3275254   .3435301 
------------------------------------------------------
----------------------------------------------------------------

. 
. 
. /*random pool of 25 units set as controls
> * drew random sample in R b/c I don't know how to do it in sta
> ta
> 
> R Code
> 
> set.seed(903)
> sample(1:51, 25, replace = FALSE)
> 
> Output from R to draw random units
> 13 28 32 20 40 48 26  1 15 30  9 36 29 23 27 12 25  6 14 17 18
>  11 37 46 10
> 
> These will be the control units for the random analysis
> */
. 
. 
. *********************
. ** OIS RATE Random **
. *********************
. synth oisp oisp(`=tm(2015m1)') oisp(`=tm(2015m2)') oisp(`=tm(2
> 015m3)') ///
> oisp(`=tm(2015m4)') oisp(`=tm(2015m5)') oisp(`=tm(2015m6)') oi
> sp(`=tm(2015m7)') ///
> oisp(`=tm(2015m8)') oisp(`=tm(2015m9)') oisp(`=tm(2015m10)') o
> isp(`=tm(2015m11)') ///
> oisp(`=tm(2015m12)') oisp(`=tm(2016m1)') oisp(`=tm(2016m2)') o
> isp(`=tm(2016m3)') ///
> oisp(`=tm(2016m4)') oisp(`=tm(2016m5)') oisp(`=tm(2016m6)') oi
> sp(`=tm(2016m7)') ///
> oisp(`=tm(2016m8)') oisp(`=tm(2016m9)') oisp(`=tm(2016m10)') o
> isp(`=tm(2016m11)') ///
> oisp(`=tm(2016m12)') oisp(`=tm(2017m1)') oisp(`=tm(2017m2)') o
> isp(`=tm(2017m3)') ///
> oisp(`=tm(2017m4)') oisp(`=tm(2017m5)') oisp(`=tm(2017m6)') oi
> sp(`=tm(2017m7)') ///
> oisp(`=tm(2017m8)') oisp(`=tm(2017m9)') oisp(`=tm(2017m10)') o
> isp(`=tm(2017m11)') ///
> oisp(`=tm(2017m12)') oisp(`=tm(2018m1)') oisp(`=tm(2018m2)') o
> isp(`=tm(2018m3)') ///
> oisp(`=tm(2018m4)') oisp(`=tm(2018m5)') oisp(`=tm(2018m6)') oi
> sp(`=tm(2018m7)') ///
> oisp(`=tm(2018m8)') oisp(`=tm(2018m9)') oisp(`=tm(2018m10)') o
> isp(`=tm(2018m11)') ///
> oisp(`=tm(2018m12)') oisp(`=tm(2019m1)') oisp(`=tm(2019m2)') o
> isp(`=tm(2019m3)') ///
> oisp(`=tm(2019m4)') oisp(`=tm(2019m5)') oisp(`=tm(2019m6)') oi
> sp(`=tm(2019m7)') ///
> oisp(`=tm(2019m8)') oisp(`=tm(2019m9)') oisp(`=tm(2019m10)') o
> isp(`=tm(2019m11)') ///
> oisp(`=tm(2019m12)'), trunit(5) trperiod(`=tm(2020m1)') counit
> (13 28 32 20 40 48 26 ///
> 1 15 30 9 36 29 23 27 12 25 6 14 17 18 11 37 46 10) figure 
----------------------------------------------------------------
Synthetic Control Method for Comparative Case Studies
----------------------------------------------------------------

First Step: Data Setup
----------------------------------------------------------------
----------------------------------------------------------------
Data Setup successful
----------------------------------------------------------------
                Treated Unit: CA
               Control Units: AK, CO, DE, FL, GA, HI, IA, ID,
                              IL, KS, KY, MA, MI, MO, MS, MT,
                              NC, ND, NE, NJ, OH, OK, RI, VA, WA
----------------------------------------------------------------
          Dependent Variable: oisp
  MSPE minimized for periods: 660 661 662 663 664 665 666 667
                              668 669 670 671 672 673 674 675
                              676 677 678 679 680 681 682 683
                              684 685 686 687 688 689 690 691
                              692 693 694 695 696 697 698 699
                              700 701 702 703 704 705 706 707
                              708 709 710 711 712 713 714 715
                              716 717 718 719
Results obtained for periods: 660 661 662 663 664 665 666 667
                              668 669 670 671 672 673 674 675
                              676 677 678 679 680 681 682 683
                              684 685 686 687 688 689 690 691
                              692 693 694 695 696 697 698 699
                              700 701 702 703 704 705 706 707
                              708 709 710 711 712 713 714 715
                              716 717 718 719 720 721 722 723
                              724 725 726 727 728 729 730 731
                              732 733 734 735 736 737 738 739
                              740 741 742 743 744 745 746 747
                              748 749 750 751 752 753 754 755
----------------------------------------------------------------
                  Predictors: oisp(660) oisp(661) oisp(662)
                              oisp(663) oisp(664) oisp(665)
                              oisp(666) oisp(667) oisp(668)
                              oisp(669) oisp(670) oisp(671)
                              oisp(672) oisp(673) oisp(674)
                              oisp(675) oisp(676) oisp(677)
                              oisp(678) oisp(679) oisp(680)
                              oisp(681) oisp(682) oisp(683)
                              oisp(684) oisp(685) oisp(686)
                              oisp(687) oisp(688) oisp(689)
                              oisp(690) oisp(691) oisp(692)
                              oisp(693) oisp(694) oisp(695)
                              oisp(696) oisp(697) oisp(698)
                              oisp(699) oisp(700) oisp(701)
                              oisp(702) oisp(703) oisp(704)
                              oisp(705) oisp(706) oisp(707)
                              oisp(708) oisp(709) oisp(710)
                              oisp(711) oisp(712) oisp(713)
                              oisp(714) oisp(715) oisp(716)
                              oisp(717) oisp(718) oisp(719)
----------------------------------------------------------------
Unless period is specified
predictors are averaged over: 660 661 662 663 664 665 666 667
                              668 669 670 671 672 673 674 675
                              676 677 678 679 680 681 682 683
                              684 685 686 687 688 689 690 691
                              692 693 694 695 696 697 698 699
                              700 701 702 703 704 705 706 707
                              708 709 710 711 712 713 714 715
                              716 717 718 719
----------------------------------------------------------------

Second Step: Run Optimization
----------------------------------------------------------------
----------------------------------------------------------------
Optimization done
----------------------------------------------------------------

Third Step: Obtain Results
----------------------------------------------------------------
Loss: Root Mean Squared Prediction Error

---------------------
   RMSPE |  .1313351 
---------------------
----------------------------------------------------------------
Unit Weights:

-----------------------
    Co_No | Unit_Weight
----------+------------
       AK |           0
       CO |        .119
       DE |           0
       FL |           0
       GA |           0
       HI |           0
       IA |           0
       ID |           0
       IL |        .069
       KS |        .127
       KY |        .012
       MA |           0
       MI |           0
       MO |           0
       MS |           0
       MT |           0
       NC |        .261
       ND |           0
       NE |        .015
       NJ |           0
       OH |        .218
       OK |         .06
       RI |           0
       VA |        .001
       WA |        .118
-----------------------
----------------------------------------------------------------
Predictor Balance:

------------------------------------------------------
                               |   Treated  Synthetic 
-------------------------------+----------------------
                     oisp(660) |   .228917   .2855722 
                     oisp(661) |   .228917   .2216703 
                     oisp(662) |   .559575   .2999434 
                     oisp(663) |  .4323989   .3466975 
                     oisp(664) |  .2034818   .1909437 
                     oisp(665) |  .2797875   .2403112 
                     oisp(666) |  .5341398   .3374434 
                     oisp(667) |  .4323989   .3426388 
                     oisp(668) |  .4578341   .1326576 
                     oisp(669) |  .5087045   .1950919 
                     oisp(670) |  .4069636   .2133352 
                     oisp(671) |   .559575   .2994236 
                     oisp(672) |  .2790371   .2591336 
                     oisp(673) |  .3805051   .3262851 
                     oisp(674) |  .2790371   .2663005 
                     oisp(675) |  .2029361   .2497425 
                     oisp(676) |  .2283031   .2092348 
                     oisp(677) |  .2029361   .3219291 
                     oisp(678) |  .3805051   .1721449 
                     oisp(679) |  .4566061   .3736186 
                     oisp(680) |  .2283031   .3289974 
                     oisp(681) |  .3044041   .2958685 
                     oisp(682) |  .3044041   .3480751 
                     oisp(683) |  .2790371   .2892942 
                     oisp(684) |  .4532419   .1982215 
                     oisp(685) |  .2769812   .5102069 
                     oisp(686) |  .4280618   .2605475 
                     oisp(687) |  .2769812   .2155603 
                     oisp(688) |  .4028817   .1199461 
                     oisp(689) |  .3525215   .3619295 
                     oisp(690) |  .3525215   .3547476 
                     oisp(691) |  .3777016   .3913152 
                     oisp(692) |  .3021613   .3019717 
                     oisp(693) |  .2518011    .324628 
                     oisp(694) |  .2518011   .1613011 
                     oisp(695) |  .3021613    .291594 
                     oisp(696) |  .2264951   .3690533 
                     oisp(697) |  .2264951   .3380851 
                     oisp(698) |  .3019935   .3036077 
                     oisp(699) |  .3271596   .2952513 
                     oisp(700) |  .1509968   .3602483 
                     oisp(701) |   .201329   .2909766 
                     oisp(702) |  .3523258   .3989715 
                     oisp(703) |  .3019935   .2640566 
                     oisp(704) |  .1006645   .2076435 
                     oisp(705) |   .201329    .195896 
                     oisp(706) |  .2516613   .2781424 
                     oisp(707) |  .2768274    .190495 
                     oisp(708) |  .3023312   .3660328 
                     oisp(709) |  .2771369   .2726962 
                     oisp(710) |  .2267484   .3306551 
                     oisp(711) |  .3023312   .2049393 
                     oisp(712) |  .2519427   .2809955 
                     oisp(713) |  .4283025   .2708074 
                     oisp(714) |  .2267484   .2810821 
                     oisp(715) |  .2771369   .3514092 
                     oisp(716) |  .1763599   .2341558 
                     oisp(717) |  .4031082    .234968 
                     oisp(718) |  .2015541   .4701546 
                     oisp(719) |  .3275254   .3291211 
------------------------------------------------------
----------------------------------------------------------------

. 
. 
. log close
      name:  <unnamed>
       log:  /Users/006489466/Desktop/CA OIS/SCMReviewerResults.
> log
  log type:  text
 closed on:  24 Aug 2023, 10:26:22
----------------------------------------------------------------
